mindtime case studies 1:12:12

®

T e c h n o l o g y t o H e l p P e o p l e U n d e r s t a n d P e o p l e

8 Case Studies

Details in these case studies have necessarily been obscured in order to protect client confiden5ality.

© 2012 MindTime Technologies Inc. Patent Pending.®

1. Building high-‐performing teamsOne of the world's leading financial management companies is worried. . . page 3

2. Understanding composi9on of survey panel popula9onA top provider of brand research communi5es suspected . . . page 6

3. Gaining ac9onable insights from customer sa9sfac9on surveyA top MBA university knew that not all students believed . . . page 9

4. Understanding brand sen9ment within communi9esA revealing look at how brands s5mulate (or don’t) . . . page 14

5. Enabling effec9ve self-‐ini9ated global collabora9onThe Chairman had fiKy-‐two heads flying in from around the world . . . page 19

6. Correla9ng thinking styles with Web traffic paIernsWho are all of these people really? Is there not a beQer way . . . page 22

7. Effec9ve messaging using MindTime audience segmenta9onBrand favorability study reveals how deeply thinking drives opinion page 25

8. Ad effec9veness study conducted in the EU and North AmericaAdver5sing effec5veness study reveals huge variance explained by MindTime page 32

Case StudiesWe are presen5ng you with a small sample of work undertaken using the MindTime Cogni5ve Framework. These studies were conducted using two MindTime technology plaWorms, one for internal HR/OD use and one for marke5ng and audience segmenta5on. If you are interested in learning more MindTime and its many uses please ask us for more informa5on.

2


CASE STUDY: Building high-‐performing teams.

The problem:

One of the world's leading financial management companies is worried aKer recently deciding that it would allow their brokers to work in teams sharing resources in the form of administra5ve assistance and junior staff.

As these teams of brokers started to form across the US, a few disquie5ng problems began to emerge. Some teams seemed to ‘click’ whereas others did not; burning through administra5ve assistants and even quickly ending in ugly feuds.

The Na5onal Head of High Net Worth (NHW) teams asked MindTime Inc. to evaluate the underlying issues, prescribe solu5ons and improve system-‐wide performance.

The plan was to measure success based on direct impact on revenue.

3


Measuring the Baseline• The Na5onal Head NHW already had data that allowed him to chart the performance of teams na5onally. Performance was measured by revenue by individual and by team. For our project the firm discounted any increase by the increase in the na5onal average.

Assessment• We mapped 20 teams. • We tagged each team with their performance data. • We then looked for correla5ons in paQerns of team make-‐up and performance using our maps. • We iden5fied the op5mal make-‐up for a team based on this early data and hypothesized as to how they were collabora5ng with their thinking to create this success.

Performance analysis• We choose a seven team sample: 2 poor performers, 2 mediocre, and 3 of the best.• We spent a total of seven days over a period of two months with each of the teams. • We observed, interviewed, discussed and evaluated how they were integra5ng team members’ thinking.

• We also coached the teams on; roles, interpersonal empathy, workflow and other dynamics making team members aware of the impact of their thinking at work.


4


The Solu.on:

Knowledge transfer and best prac9ces implementa9on• MindTime developed an Op5mal Thinking Style distribu5on for High Net Worth Teams• We mapped each of the teams against this and recommended changes for some teams• We also developed a set of best prac5ces for collabora5on and informa5on sharing based on MindTime principles

• In concluding the project we held a teams forum off site bringing teams in from around the country

• We also shared with each team what we had learned from the other teams• This resulted in the development of an informal informa5on network among teams across the country. The purpose of this network was to share insights and best prac5ces, support and discuss issues and foster a culture of team collabora5on across the organiza5on.

Results• Within two months we had started to see significant improvement• Revenue increased between 14-‐23% over the na5onal baseline average for the period. • The most improved performance came from the best teams. While they were already top performers the added knowledge and confidence of knowing why they were succeeding had them push even harder in all the right ways.

• The MindTime® method was then deployed across more than 60 of the firm’s top teams.


5


CASE STUDY: Understanding composi9on of survey panel popula9on.

The problem:

A top provider of brand research communi5es suspected that any one of their given communi5es did not necessarily represent the popula5on at large. Their concern remained despite the fact that they had gone to great pains to recruit (an on-‐going task) people who, by all other demographics, seemed to represent the popula5on at large.

6


Assessment• All par5cipants (255) were asked to complete the GPS for the Mind.• Other client specific data was captured.• Analysis of the data is on going, but we have used our MAP to show some very early basic findings from a quick evalua5on of the distribu5on of thinking styles.

Parameters• The surveyed popula5on is a general community and not 5ed specifically to one brand.

7



Survey panel at research company

Brief analysis• The panel popula5on is showing a marked skew towards Past & Present thinking.

• Even integrated thinking is showing a strong bias towards Past & Present perspec5ves.

• The sample is small (255) but that is the average (low) size of a marke5ng panel, this bias should be taken seriously, it could fundamentally affect results of any research conducted.

• Community member responses in any study conducted will show a bias towards conserva5sm, risk aversion, need for informa5on, organiza5on, tradi5onalism, process orienta5on, and an aQrac5on to authority or the educa5onal qualifica5ons of people.

• The thinking styles most represented in the survey panel are more likely to belong to this kind of brand research community in the first place.

• Future thinkers would likely not be aQracted to belong to these kinds of community. They might sign up, but they would not likely show up.

255 people

8


Future

Present

Past


CASE STUDY: Gaining new ac9onable insights from a customer sa9sfac9on survey.

The problem:

A top MBA university knew that not all students believed that they were receiving a good educa5on given its cost. Certain feedback from students had indicated that some felt it sub standard, but because of their exis5ng investment tended to s5ck it out. The university grew concerned that their reputa5on would suffer in the local community from bad word of mouth. Given the 5ghtly knit nature of the business community this concern was probably warranted. Their biggest fear was that student reten5on would suffer in the face of compe55on who were rumored to be accep5ng transfers from other MBA programs.

9


Assessment• We asked all students in two MBA programs (74) to complete the GPS for the Mind.• We also captured the following data: Professor, age bracket, gender• We used MindTime Maps capability to collect amtudinal data from the par5cipants. A panel of items was developed to look at various aspects of their experience at the university.

Analysis• We mapped all par5cipants in a Map of the World of thinking.

• Our MAP revealed nothing special about the distribu5on of this group of students.

• A fairly typical picture of middle management thinking styles from both engineering and business backgrounds

10


Future

Present

Past


• Analysis of responses on the ques5on of perceived value of the educa5on did not show any correla5on between class they were enrolled in or gender or age.

Analysis con9nued . . .

11



• Analysis of responses on the ques5on of perceived value of the educa5on did show marked correla5on with thinking style.

• Past thinkers were clearly the most (and only) dissa5sfied group of students.

• Present/Futures showed the greatest sa5sfac5on with value delivered.

*

**

*

12



• A second look at our MAP analysis revealed the likely cause of student dissa5sfac5on.

• The Professor (who taught both MBA classes) had a Future thinking style.

• On further inves5ga5on (through confiden5al conversa5ons with Past thinking respondents) it became clear that the professors thinking style did not align with Past thinkers needs, nor did it feel authorita5ve, thus undermining students’ confidence.

• Further, Past thinking students reported that the curriculum was presented in a style which precluded them from gaining a deep grasp of the subjects being taught. “Too much talk and not enough hard facts,” said one respondent.

Analysis con9nued . . .

*

*

13


Future

Present

Past


CASE STUDY: Understanding brand sen9ment within communi9es.

The problem:

A major brand research community provider asked us to help them test whether people’s percep5ons and thoughts had an effect on the sen5ments they expressed about various brands. At the core of this study were two ques5ons.

Does a person’s thinking style significantly drive their sen5ments on a given brand?Is it possible to iden5fy the fundamental values (as iden5fied by the MindTime framework) of people who most resonate with a given brand?

14


Assessment• 255 people were mapped using the GPS for the Mind.• All par5cipants were asked to respond with a favorability ra5ng for 10 separate brands on a scale of 1-‐5 (1 being least and 5 being most favored).• Gender, age and race were known data about this community and were provided to us for analysis.

Data analysis -‐ Group composi9on and sen9ment• A series of standard sta5s5cal techniques (ANOVA, regression, variance, etc) was used to analyze the data.

• It was noted that there were not enough respondents in the sample to be able to consistently show sta5s5cal significance in all demographic groups (race, age, gender).

15



16

*

* Extroverted, posi5ve, organized, deliberate, liberal, social, energe5c, inven5ve people liked VW. They were Future/Present thinkersIntroverted, studious, bookish, informed, analy5cal, risk averse, knowledgable, detailed people were less sold

Favorability by Thinking Style

We used data on the Volkswagen brand data as our example

Findings

Across a majority of brands tested thinking style was found to have a sta5s5cally significant impact on people’s ra5ng of brands.In this excerpted example we can see that Future Present people rated the brand most favorably, and Past thinkers least favorably.



17

*

Where men exhibit higher favorability ra5ngs than women the influence of—image, novelty, fun, hip, extraversion, trend semng, speedy—is strongest.

*

$ If this data were SmartSliced by age and socio-‐economic status we’d really be zeroing in on some very potent insights.

Where women exhibit higher favorability ra5ngs than men the influence of—prac5cal, affordable, recommended by other consumers, well built (German), trendy, social, “right”—is strongest.

FemalesMales

Findings con9nued . . .



18

We know from other studies that opinions, beliefs, amtudes and values are also driven by these same influences

If MindTime is explaining this amount of variance in sen5ment data, we can reasonably speculate that thinking style is having a very large impact on all other aspects of a brand’s messaging.

Variance Explained1.1) Volkswagen 5.90%1.2) BMW 12.40%1.3) Hyundai 6.80%1.4) Apple 6.20%1.5) MicrosoL 2.00%1.6) Coca Cola 1.70%1.7) Dunkin’ Donuts 1.80%1.8) Tropicana 4.20%1.9) Levis 3.40%1.10) Southwest Airlines 6.90%1.11) UPS 0.90%1.12) Heinz 1.50%1.13) Budweiser 1.70%1.14) JC Penny 2.40%1.15) Amazon 2.80%

*

This chart shows the amount of variance in favorability among respondents that can be explained by thinking profile data over and above the influence of all other demographic factors

**Findings con9nued . . .



CASE STUDY: Enabling effec9ve self-‐ini9ated global collabora9on.

The problem:

The Chairman had fiKy-‐two heads flying in from around the world, the top bosses of his global divisions, for the annual pow-‐wow of the global brass. The issue he presented to us was as follows.

While each and every one of these highly paid, educated and experienced individuals was performing at a superla5ve level, there was a lack of collabora5on between them on a global basis. The Chairman of the Board and CEO felt that his ‘team’ weren't fully apprecia5ng the value each could bring to the others in managing their divisions. They were not leveraging opportuni5es collabora5vely. He asked if we could help raise the level of their awareness to see that it was more than just sales opportuni5es they needed to share with each other. He wanted all of his top management to understand that there was huge opportunity in sharing their knowledge and experience from the point of view of their thinking style driven perspec5ves.

19


Assessment• We asked all par5cipants (56) to complete the GPS for the Mind.• We also captured data on length of service, posi5on held, we also asked par5cipants to rank their peers by whom they spoke to most frequently (1st, 2nd, 3rd.)

• We developed a series of maps that showed the overall make-‐up of global senior management, by country, by frequency (rank) of inter-‐personal contact, and by posi5on.

The Solu.on:

Knowledge Transfer• We designed and facilitated a half-‐day workshop delivered in Florida at their annual mee5ng.• During the workshop we asked all par5cipants to list at least three instances when the thinking perspec5ve they were most resistant to (the perspec5ve they had the least of) had goQen them in trouble.

• We then went through a standard presenta5on of MindTime highligh5ng the role of the thinking perspec5ves in business and life.

• We shared the maps we had prepared with par5cipants and had a broad and open discussion.• Par5cipants were asked to work in groups of diverse thinking styles sharing their three failure scenarios and listening to each other’s input.


20


Results• It was obvious to par5cipants that they were communica5ng on a far more frequent basis with peers who shared their own perspec5ve.

• These ‘like minded’ conversa5ons were more in-‐depth and covered a broader range of topics.

• Data showed that geography had no bearing on the frequency of people’s communica5on; no maQer how geographically dispersed from one another they discovered they had been reaching out to peers of like thinking style.

• Par5cipants overwhelmingly reported gaining an apprecia5on for how others saw reported situa5ons and how nega5ve impacts might have been avoided if a broader set of thinking skills being applied at the outset.

• Each par5cipant iden5fied four individuals in the group who held a perspec5ve which was least like their own. Over the course of the next three days they spent “immersion” 5me gemng to know these others in conversa5on and meals together.

• An overall map of the senior management team revealed that there was no imbalance of thinking perspec5ves across the group. However, the Chairman did reveal that divisions led by Future thinkers were more likely to have erra5c but stunning results, while those led by Present and Past leaders had beQer long-‐term and more consistent successes.


21


22

CASE STUDY: Correla9ng thinking styles with Web traffic paIerns.

The problem:

Who are all of these people really? Is there not a beQer way to understand why they do what they do in Web sites? Hundreds of millions of dollars are spent developing sophis5cated Web environments with only the most primi5ve models of human behavior being used to understand the users they serve.

We set about crea5ng an internal case study to explore what the data would show if we did even a cursory analysis of the web traffic in our own site. The results are very encouraging that MindTime will provide new predic5ve and rela5onal analy5c capability for building beQer Web experiences for users.


Assessment• We asked visitors (222) to our web site to complete the GPS for the Mind.• We used Google Analy5cs custom variable fields to import MindTime data into Google Analy5cs applica5on.

• We separated the data into the ten archetype MindTime model.• We then ran the system for a few days and collected the data.• Analysis was done using Google Analy5cs PlaWorm.

Parameters• We used our 18 item version of the GPS for the Mind (a 9 item version is available).• Our audience tends to be skewed towards Future and Future/Present thinkers. This is a func5on of the business audience who traffics our site.

23



24

NEW DATA


Analysis• There is clear behavioral differen5a5on between thinking styles.• There is clear difference between the ten archetypes in avg. number of pages visited, avg. 5me on site, and the bounce rate.


The TestAn interna5onally Telcom brand wanted to understand how well two compe5ng sets of adver5sing ideas—one designed to conform with MindTime audience segmenta5on and one not—would be received by small business decision makers (10-‐100 employees) in the USA.

Beyond simply wan5ng to understand how the two sets of compe5ng ad ideas were received—if one of the sets of ad ideas liKed the audience’s sen5ments on specific differen5a5ng brand aQributes more than the other—the client also wanted to gain insight into how the audience’s thinking was being influenced by the ad ideas presented. And, they wanted to know why the ads might be influencing’ (s5mula5ng and changing percep5ons) in certain kinds of people—driving higher sen5ment responses—while leaving others unaffected by the ad ideas—with resul5ng low or no liK in sen5ment.

To put all of this more straighWorwardly. The brand wanted to understand how targe5ng people’s thinking, through using MindTime audience segmenta5on, ad design and messaging principles, can influence brand sen5ment and behavioral outcomes.

25CASE STUDY: Effec9ve messaging using MindTime audience segmenta9on


Our hypothesis• We hypothesized that small business decision makers are most driven by Present and Future thinking—using the nomenclature of our model. Years of mapping audiences and businesses bears this hypothesis out. Thus an adver5sement designed with the needs of these thinking perspec5ves in mind would create more liK in the targeted audience than an ad not specifically designed for this target audience.

Research design• A na5onal market research firm was engaged to conduct the study, this included recrui5ng the panel audience (specifically filtering for small business decision makers) and running the study.

• Six adver5sement ideas were prepared by the adver5sing agency that represents the brand. All ads targeted small business decision makers. Three were designed with no thinking style bias (“Calling Card” Concept A). Three were especially designed using MindTime design principals to influence Future and Present thinkers (“Outcomes” Concept B).

• 525 people were recruited and surveyed, 353 of the respondents were used in the study (not all conformed with the client’s desired demographic mix).

• The panel was randomly split into two roughly equal groups. • Respondents in both groups were first profiled with the MindTime profile, then both groups were asked to react to 11 brand aQributes that were deemed to be of importance.

• Half the respondents were then shown the three versions of the ‘MindTime guided design’ ad idea (Concept B), the other half were shown the non-‐MindTime ad idea (Concept A). Having seen the ‘s5mulus’ material they were all asked to give their reac5on again to the same 11 brand aQribute ques5ons.

• An 8 point Likert scale was used to measure par5cipants responses to brand aQribute ques5ons.

26CASE STUDY: Effec9ve messaging using MindTime audience segmenta9on


27

Concept A“Calling Card”

Concept B“Outcomes”

The ad concepts

Client protection Client protection Client protection

Client protection Client protection Client protection

CASE STUDY: Effec9ve messaging using MindTime audience segmenta9on

Designed using MindTime Design Principals


28

The research panel audience composi9on

Pa Fu

Pr



29

Visualiza9on of audience li[ in sen9ment using MindTime® thermo maps™

Pr Pr

Pre Exposure Post Exposure

Pa Fu Pa Fu

Intensity and size of popula5on engaging with “Outcomes” (Concept B) increased drama5cally.

Increased favorability in brand aQribute “Enables the Flexibility I want” (concept B)


The hypothesized target audience of small business decision makers


30

How much did thinking style drive people’s percep9ons?Percent variance explained by thinking perspective on the 11 business related items both before (pre) and after (post) exposure to Concept 1 and Concept 2. Percent variance explained by thinking perspective on the 11 business related items both before (pre) and after (post) exposure to Concept 1 and Concept 2. Percent variance explained by thinking perspective on the 11 business related items both before (pre) and after (post) exposure to Concept 1 and Concept 2. Percent variance explained by thinking perspective on the 11 business related items both before (pre) and after (post) exposure to Concept 1 and Concept 2. Percent variance explained by thinking perspective on the 11 business related items both before (pre) and after (post) exposure to Concept 1 and Concept 2.

Brand attribute measured Pre- Exposure to ConceptPre- Exposure to Concept Post-Exposure to ConceptPost-Exposure to ConceptConcept 1 Concept 2 Concept 1 Concept 2

Provides solutions for a business like mine .072 .050 .070 .076*

Is an advocate for my small business .065 .080* .035 .085*

Understands my priorities .054 .088* .048 .121*

Helps me realize new opportunities .086* .079* .065* .099*Has the best selection .067 .065 .081* .086*

Recognizes my business objectives .064 .100* .056 .082*Enables the flexibility want .066 .058 .056 .093*

Has quality products and services .057 .061 .049 .082*Is a brand/company I trust .043 .059 .038 .042

Will be there for me. .063 .073 .035 .094*

Helps me feel confident .048 .071 .048 .088*



31

Charts of li[ by thinking style (pre and post ad exposure)

Increased favorability in brand aQribute “Enables the Flexibility I want” (concept B)

Enables the flexibility I want (Concept B) Enables the flexibility I want (Concept B)

Pre Post

The hypothesized target audience of small business decision makers



32CASE STUDY: Ad effec9veness study conducted in Germany, France and North America

Does thinking maIer?

While we all can readily understand how being a man or a woman, being young or older, or being rich or poor might impact our decisions, it is perhaps not so immediately obvious how our thinking style affects our perceptions and the choices we make.

In the following case study MindTime Technologies participated with a global ad planning company, a global digital research company and a global advertising company to asses the degree to which MindTime archetype was accounting for people’s behaviors in an advertising effectiveness study conducted on behalf of a client in Germany, France and North America.



MethodologySurvey respondents were recruited online. They were divided into those who had been exposed to the advertisement and those who had not (control group).Opinions, intent, brand favorability, and thinking style were then measured in a survey.Respondents were segmented using MindTime’s 8 archetype model.

• Map shows distribution of audience sample of 1,500 (North America data) people who participated in the study

• Target audience CTO/decision makers in start-ups and small businesses

• Target thinking style presumed to be Past/Present

Target audience



* Statistically significant difference between control and exposed group at a 90% confidence level

- Insufficient Sample for Reporting

ResonanceWhile the target audience was Past/Present in make up, the ads resonated with Future thinkers, and did so very well. The ads were deemed to be off market and were redesigned using MindTime design principals.

Ad resonance

Ad target



TimeStyle,*58.62%*

Age,*0.00%*

Gender,*0.00%*

Income,*24.14%*

Work*Status,*17.24%*

Exposure,*0.00%*

How$would$you$describe$your$overall$opinion$about$.net$Propor6on$of$total$variance$explained$

TimeStyle*

Age*

Gender*

Income*

Work*Status*

Exposure*

• Total amount of people’s responses explained by all measured variables: 5.8%

• Of the above, thinking style explained: 58.62%

• The amount of people’s responses explained due to interactions between thinking style and the other measured variables: 19.70%

Variance Explained in People’s Opinions (North American Data)



TimeStyle,*41.33%*

Age,*12.00%*Gender,*0.00%*

Income,*22.67%*


Exposure,*2.67%*

The$next$(me$you$are$planning$to$register$a$website,$$how$likely$are$you$to$consider$.net$

Propor(on$of$total$variance$explained$

TimeStyle*

Age*

Gender*

Income*

Work*Status*

Exposure*

• Total amount of people’s responses explained by measured variables: 7.5%

• Of the above, thinking style explained the following proportion: 41.33%

• The amount of people’s responses explained due to interactions between thinking style and the other variables: 22.85%

Variance Explained in People’s Intent (North American Data)



TimeStyle,*35.96%*

Age,*6.74%*

Gender,*2.25%*Income,*24.72%*


Exposure,*20.22%*

How$strongly$do$you$agree$that$.net$is$[brand$a5ribute]$Propor9on$of$total$variance$explained$(average)$

TimeStyle*

Age*

Gender*

Income*

Work*Status*

Exposure*

• Total amount of people’s responses explained by measured variables: 8.9%.

• Of the above, thinking style explained the following proportion: 35.96%

• The amount of people’s responses explained due to interactions between thinking style and the other variables: 9.61%

Variance Explained in Brand Attributes (North America Data)


Try it . . .

Thank you.

Visit our mapping site to learn about your own thinking style and how it affects your life— www.mindtimemaps.com

John Furey, CEOMindTime Technologies [email protected]

To learn more about business opportuni5es, contact:

38

mindtime case studies 1:12:12

Documents

performance of teams

best teams

teams of brokers

mindtime page

mindtime technologies

teams forum o site

mindtime principles

mindtime method